In-silico design and ADMET predictions of some new imidazo[1,2-a]pyridine-3-carboxamides (IPAs) as anti-tubercular agents

In-silico molecular modelling studies of some camphor imine based compounds as anti-influenza A (H1N1) pdm09 virus agents

The advent of influenza A (H1N1) drug-resistant strains led to the search quest for more potent inhibitors of the influenza A virus, especially in this devastating COVID-19 pandemic era. Hence, the present research utilized some molecular modelling strategies to unveil new camphor imine-based compounds as anti-influenza A (H1N1) pdm09 agents. The 2D-QSAR results revealed GFA-MLR (R2train = 0.9158, Q2=0.8475) and GFA-ANN (R2train = 0.9264, Q2=0.9238) models for the anti-influenza A (H1N1) pdm09 activity prediction which have passed the QSAR model acceptability thresholds. The results from the 3D-QSAR studies also revealed CoMFA (R2train =0.977, Q2=0.509) and CoMSIA_S (R2train =0.976, Q2=0.527) models for activity predictions. Based on the notable information derived from the 2D-QSAR, 3D-QSAR, and docking analysis, ten (10) new camphor imine-based compounds (22a-22j) were designed using the most active compound 22 as the template. Furthermore, the high predicted activity and binding scores of compound 22j were further justified by the high reactive sites shown in the electrostatic potential maps and other quantum chemical calculations. The MD simulation of 22j in the active site of the influenza hemagglutinin (HA) receptor confirmed the dynamic stability of the complex. Moreover, the appraisals of drug-likeness and ADMET properties of the proposed compounds showed zero violation of Lipinski's criteria with good pharmacokinetic profiles. Hence, the outcomes in this work recommend further in-depth in vivo and in-vitro investigations to validate these theoretical findings.Communicated by Ramaswamy H. Sarma.

Phytochemical characterization of Typha domingensis and the assessment of therapeutic potential using in vitro and in vivo biological activities and in silico studies

Typha domingensis, a medicinal plant with significant traditional importance for curing various human diseases, has potentially bioactive compounds but was less explored previously. Therefore, this study aims to investigate the therapeutic potential of T. domingensis by evaluating the phytochemical profile through high-performance liquid chromatography (HPLC) techniques and its biological activities (in vitro and in vivo) from the methanolic extract derived from the entire plant (TDME). The secondary metabolite profile of TDME regulated by reverse phase ultra-high-performance liquid chromatography-mass spectrometry (RP-UHPLC-MS) revealed some bioactive compounds by -ve and +ve modes of ionization. The HPLC quantification study showed the precise quantity of polyphenols (p-coumaric acid, 207.47; gallic acid, 96.25; and kaempferol, 95.78 μg/g extract). The enzyme inhibition assays revealed the IC50 of TDME as 44.75 ± 0.51, 52.71 ± 0.01, and 67.19 ± 0.68 µgmL-1, which were significant compared to their respective standards (indomethacin, 18.03 ± 0.12; quercetin, 4.11 ± 0.01; and thiourea, 8.97 ± 0.11) for lipoxygenase, α-glucosidase, and urease, respectively. Safety was assessed by in vitro hemolysis (4.25% ± 0.16% compared to triton × 100, 93.51% ± 0.36%), which was further confirmed (up to 10 g/kg) by an in vivo model of rats. TDME demonstrated significant (p < 0.05) potential in analgesic activity by hot plate and tail immersion tests and anti-inflammatory activity by the carrageenan-induced hind paw edema model. Pain latency decreased significantly, and the anti-inflammatory effect increased in a dose-dependent way. Additionally, in silico molecular docking revealed that 1,3,4,5-tetracaffeoylquinic acid and formononetin 7-O-glucoside-6″-O-malonate possibly contribute to enzyme inhibitory activities due to their higher binding affinities compared to standard inhibitors. An in silico absorption, distribution, metabolism, excretion, and toxicological study also predicted the pharmacokinetics and safety of the chosen compounds identified from TDME. To sum up, it was shown that TDME contains bioactive chemicals and has strong biological activities. The current investigations on T. domingensis could be extended to explore its potential applications in nutraceutical industries and encourage the isolation of novel molecules with anti-inflammatory and analgesic effects.

Computational modelling studies of some 1,3-thiazine derivatives as anti-influenza inhibitors targeting H1N1 neuraminidase via 2D-QSAR, 3D-QSAR, molecular docking, and ADMET predictions

Background

Influenza virus disease remains one of the most contagious diseases that aided the deaths of many patients, especially in this COVID-19 pandemic era. Recent discoveries have shown that the high prevalence of influenza and SARS-CoV-2 coinfection can rapidly increase the death rate of patients. Hence, it became necessary to search for more potent inhibitors for influenza disease therapy. The present study utilized some computational modeling concepts such as 2D-QSAR, 3D-QSAR, molecular docking simulation, and ADMET predictions of some 1,3-thiazine derivatives as inhibitors of influenza neuraminidase (NA).

Results

The 2D-QSAR modeling results showed GFA-MLR ($$R_{{\text{train }}}^{2}$$ R train 2  = 0.9192, Q2 = 0.8767, R2adj = 0.8991, RMSE = 0.0959, $$R_{{{\text{test}}}}^{2}$$ R test 2  = 0.8943, $$R_{{{\text{pred}}}}^{2}$$ R pred 2  = 0.7745) and GFA-ANN ($$R_{{\text{train }}}^{2}$$ R train 2  = 0.9227, Q2 = 0.9212, RMSE = 0.0940, $$R_{{{\text{test}}}}^{2}$$ R test 2  = 0.8831, $$R_{{{\text{pred}}}}^{2}$$ R pred 2  = 0.7763) models with the computed descriptors as ATS7s, SpMax5_Bhv, nHBint6, and TDB9m for predicting the NA inhibitory activities of compounds which have passed the global criteria of accepting QSAR model. The 3D-QSAR modeling was carried out based on the comparative molecular field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA). The CoMFA_ES ($$R_{{\text{train }}}^{2}$$ R train 2  = 0.9620, Q2 = 0.643) and CoMSIA_SED ($$R_{{\text{train }}}^{2}$$ R train 2  = 0.8770, Q2 = 0.702) models were found to also have good and reliable predicting ability. The compounds were also virtually screened based on their binding scores via molecular docking simulations with the active site of the NA (H1N1) target receptor which also confirms their resilient potency. Four potential lead compounds (4, 7, 14, and 15) with the relatively high inhibitory rate (> 50%) and docking (> − 6.3 kcal/mol) scores were identified as the possible lead candidates for in silico exploration of improved anti-influenza agents.

Conclusion

The drug-likeness and ADMET predictions of the lead compounds revealed non-violation of Lipinski’s rule and good pharmacokinetic profiles as important guidelines for rational drug design. Hence, the outcome of this research set a course for the in silico design and exploration of novel NA inhibitors with improved potency.

In-silico modelling studies of 5-benzyl-4-thiazolinone derivatives as influenza neuraminidase inhibitors via 2D-QSAR, 3D-QSAR, molecular docking, and ADMET predictions

Influenza virus disease is one of the most infectious diseases responsible for many human deaths, and the high mutability of the virus causes drug resistance effects in recent times. As such, it became necessary to explore more inhibitors that could avert future influenza pandemics. The present research utilized some in-silico modelling concepts such as 2D-QSAR, 3D-QSAR, molecular docking simulation, and ADMET predictions on some 5-benzyl-4-thiazolinone derivatives as influenza neuraminidase (NA) inhibitors. The 2D-QSAR modelling results revealed GFA-MLR (R train 2 =0.8414, Q2 = 0.7680) and GFA-ANN (R train ​ 2 =0.8754, Q2 = 0.8753) models with the most relevant descriptors (MATS3i, SpMax5_Bhe, minsOH and VE3_D) for predicting the inhibitory activities of the molecules which has passed the global criteria of accepting QSAR models. The results of the 3D-QSAR modelling results showed that CoMFA_ES (R train ​ 2 =0.9030, Q2 = 0.5390) and CoMSIA_EA (R train 2 =0.880, Q2 = 0.547) models are having good predicting ability among other developed models. The molecules were virtually screened via molecular docking simulation with the active site of NA protein receptor (pH1N1) which confirms their resilient potency when compared with zanamivir standard drug. Molecule 11 as the most potent molecule formed more H-bond interactions with the key residues such as TRP178, ARG152, ARG292, ARG371, and TYR406 that triggered the catalytic reactions for NA inhibition. Furthermore, six (6) molecules (9, 10, 11, 17, 22, and 31) with relatively high inhibitory activities and docking scores were identified as the possible leads for in-silico exploration of novel NA inhibitors. The drug-likeness and ADMET predictions of the lead molecules revealed non-violation of Lipinski's rule and good pharmacokinetic profiles respectively, which are important guidelines for rational drug design. Hence, the outcome of this study overlaid a solid foundation for the in-silico design and exploration of novel NA inhibitors with improved potency.

A new exploration toward adamantane derivatives as potential anti-MDR agents: Design, synthesis, antimicrobial, and radiosterilization activity as potential topoisomerase IV and DNA gyrase inhibitors

Developing novel antimicrobial agents has become a necessitate due to the increasing rate of microbial resistance to antibiotics. All the newly adamantane derivatives were evaluated for their antimicrobial activities against six MDR clinical pathogenic isolates. The results exhibited that 13 compounds have from potent to good activity. Among those, five derivatives (6, 7, 9, 14a, and 14b) displayed the potent activities against the different isolates tested (MIC < 0.25 µg/ml with bacteria and <8 µg/ml with fungi) compared with Ciprofloxacin (CIP) and Fluconazole (FCA). Additionally, the potent adamantanes showed bactericidal and fungicidal effects based on (MBCs and MFCs) and the time-kill assay. The most active adamantane derivatives 7 and 14b exhibited a synergistic effect of ΣFIC ≤ 0.5 with CIP and FCA against the bacterial and fungal isolates. Moreover, no antagonistic effect appeared for the tested derivatives. Additionally, the interaction of DNA gyrase and topoisomerase IV enzymes with the compounds 6, 7, 9, 14a, and 14b exhibited potent antimicrobial activity using in vitro biochemical assays and gel-based DNA-supercoiling inhibition method. The activity of DNA gyrase and topoisomerase IV enzymes showed inhibitory activity (IC₅₀ ) of 6.20 µM and 9.40 µM with compound 7 and 10.14 µM and 13.28 µM with compound 14b, respectively. Surprisingly, exposing compound 7 to gamma irradiation sterilized and increased its activity. Finally, the in-silico analysis predicted that the most active derivatives had good drug-likeness and safe properties. Besides, molecular docking and quantum chemical studies revealed several important interactions inside the active sites and showed the structural features necessary for activity.